1 Introduction

This paper contains estimates for the effective reproduction number \(R_{t,m}\) over time \(t\) in various nations and other regions \(m\) of United Kingdom. This is done using the methodology as described in [1]. These have been implemented in R using EpiEstim package [2] which is what is used here. The methodology and assumptions are described in more detail here.

This paper and it’s results should be updated roughly daily and is available online.

As this paper is updated over time this section will summarise significant changes. The code producing this paper is tracked using Git. The Git commit hash for this project at the time of generating this paper was b141aff519ee125929b3b6f686b1070f3fc70742.

2 Data

Data is obtained [3]. This contains the daily cases, hospital admissions and deaths for United Kingdom by various geographies. Here the data is accessed by specimen date, admission date and date of death.

Once history is built up an allowance for rate reported cases, admissions and deaths will be made. For now the data is cut-off a week prior to the last case date in the data. All data prior to 1 March 2020 are removed.

3 Methodology

The methodology is described in detail here.

4 Results by Nation

4.1 Cases

Below a 7-day moving average of daily case count on a log scale by nation is plotted:

Daily Cases by Nation (7-day moving average)

Daily Cases by Nation (7-day moving average)

4.2 Admissions

Below we plot cumulative hospital admissions on a log scale.

Daily Admissions by Nation (7-day moving average)

Daily Admissions by Nation (7-day moving average)

4.3 Deaths

Below a 7-day moving average of daily deaths by nation on a log scale is plotted:

Daily Deaths by Nation (7-day moving average)

Daily Deaths by Nation (7-day moving average)

4.4 Current \(R_{t,m}\) estimates by Nation

Below current (last weekly) \(R_{t,m}\) estimates are tabulated.

Estimated Effective Reproduction Number by Nation
Nation Estimate Type Count (Last Week) Week Ending R - Lower CI R - Mean R - Uppper CI
England cases 13,571 2021-04-17 0.8 0.8 0.9
England admissions 1,037 2021-04-17 0.8 0.9 0.9
England deaths 116 2021-04-17 0.7 0.8 1.0
Northern Ireland cases 789 2021-04-17 1.0 1.1 1.2
Northern Ireland admissions 25 2021-04-17 0.6 0.9 1.2
Northern Ireland deaths 7 2021-04-17 0.4 0.9 1.6
Scotland cases 1,560 2021-04-17 0.8 0.8 0.9
Scotland admissions 84 2021-04-17 0.6 0.7 0.9
Scotland deaths 9 2021-04-17 0.4 0.8 1.3
Wales cases 471 2021-04-17 0.8 0.9 0.9
Wales admissions 109 2021-04-17 0.8 1.0 1.2
Wales deaths 8 2021-04-17 0.5 1.0 1.8
Estimated Effective Reproduction Number by Nation

Estimated Effective Reproduction Number by Nation

4.5 Maps of Effective Reproduction Number

Below we plot the current effective reproduction number on maps with boundaries provided by [4].

4.5.1 Cases

4.5.2 Admissions

4.5.3 Deaths

4.6 Graphs over Time

Below we plot results for each nation We filter out weeks where the upper end of confidence interval for \(R_{t,m}\) exceeds 4.

4.6.1 England

4.6.2 Northern Ireland

4.6.3 Scotland

4.6.4 Wales

5 Results by Region

5.1 Cases

Below we daily case count is plotted on a log scale by region:

Daily Cases by Region (7-day moving average)

Daily Cases by Region (7-day moving average)

5.2 Deaths

Below a 7-day moving average of daily deaths by region is plotted on a log scale:

Daily Deaths by Region (7-day moving average)

Daily Deaths by Region (7-day moving average)

5.3 Current \(R_{t,m}\) estimates by Region

Below current (last weekly) \(R_{t,m}\) estimates are tabulated.

Estimated Effective Reproduction Number by Region
Region Estimate Type Count (Last Week) Week Ending R - Lower CI R - Mean R - Uppper CI
Northern Ireland cases 789 2021-04-17 1.0 1.1 1.2
Northern Ireland deaths 7 2021-04-17 0.4 0.9 1.6
Scotland cases 1,560 2021-04-17 0.8 0.8 0.9
Scotland deaths 9 2021-04-17 0.4 0.8 1.3
Wales cases 471 2021-04-17 0.8 0.9 0.9
Wales deaths 8 2021-04-17 0.5 1.0 1.8
North East cases 614 2021-04-17 0.8 0.8 0.9
North East deaths 4 2021-04-17 0.2 0.7 1.5
North West cases 1,870 2021-04-17 0.8 0.8 0.9
North West deaths 19 2021-04-17 0.4 0.7 1.1
Yorkshire and The Humber cases 2,578 2021-04-17 0.8 0.8 0.8
Yorkshire and The Humber deaths 36 2021-04-17 0.8 1.1 1.5
East Midlands cases 1,400 2021-04-17 0.7 0.8 0.8
East Midlands deaths 9 2021-04-17 0.2 0.5 0.9
West Midlands cases 1,319 2021-04-17 0.8 0.8 0.9
West Midlands deaths 12 2021-04-17 0.7 1.4 2.2
East of England cases 1,274 2021-04-17 0.8 0.9 0.9
East of England deaths 8 2021-04-17 0.4 0.9 1.5
London cases 2,014 2021-04-17 0.9 0.9 1.0
London deaths 10 2021-04-17 0.5 1.0 1.6
South East cases 1,545 2021-04-17 0.8 0.9 0.9
South East deaths 8 2021-04-17 0.3 0.6 1.0
South West cases 723 2021-04-17 0.9 0.9 1.0
South West deaths 9 2021-04-17 0.5 1.1 1.9
Estimated Effective Reproduction Number by Region

Estimated Effective Reproduction Number by Region

5.4 Maps of Effective Reproduction Number

Below we plot the current effective reproduction number on maps with boundaries provided by [5].

5.4.1 Cases

5.4.2 Deaths

5.5 Graphs over Time

Below we plot results for each nation.

5.5.1 Northern Ireland

5.5.2 Scotland

5.5.3 Wales

5.5.4 North East

5.5.5 North West

5.5.6 Yorkshire and The Humber

5.5.7 East Midlands

5.5.8 West Midlands

5.5.9 East of England

5.5.10 London

5.5.11 South East

5.5.12 South West

6 Results by NHS Region

6.1 Current \(R_{t,m}\) estimates by Region

Below current (last weekly) \(R_{t,m}\) estimates are tabulated.

Estimated Effective Reproduction Number by Region
Region Estimate Type Count (Last Week) Week Ending R - Lower CI R - Mean R - Uppper CI
Northern Ireland admissions 25 2021-04-17 0.6 0.9 1.2
Scotland admissions 84 2021-04-17 0.6 0.7 0.9
Wales admissions 109 2021-04-17 0.8 1.0 1.2
North West admissions 137 2021-04-17 0.7 0.8 1.0
East of England admissions 147 2021-04-17 1.0 1.1 1.3
London admissions 132 2021-04-17 0.7 0.8 0.9
South East admissions 105 2021-04-17 0.7 0.9 1.1
South West admissions 71 2021-04-17 0.8 1.0 1.3
Midlands admissions 204 2021-04-17 0.7 0.9 1.0
North East and Yorkshire admissions 241 2021-04-17 0.7 0.8 0.9
Estimated Effective Reproduction Number by Region

Estimated Effective Reproduction Number by Region

6.2 Maps of Effective Reproduction Number

Below we plot the current effective reproduction number on maps with boundaries provided by [6].

6.3 Graphs over Time

Below we plot results for each nation We filter out weeks where the upper end of confidence interval for \(R_{t,m}\) exceeds 4.

6.3.1 London

6.3.2 South East

6.3.3 South West

6.3.4 East of England

6.3.5 Midlands

6.3.6 North East and Yorkshire

6.3.7 North West

7 Results by Upper Tier Local Authority

7.1 Highest \(R_{t,m}\) as estimated using cases

Below we plot Upper Tier Local Authorities with the highest reproduction numbers (providing they had at least 100 cases in last 7 days):

## Selecting by Rt_ui_95
Estimated Effective Reproduction Number by Upper Tier Local Authority
Upper Tier Local Authority Estimate Type Count (Last Week) Week Ending R - Lower CI R - Mean R - Uppper CI
Mid Ulster cases 88 2021-04-17 1.1 1.4 1.7
Cornwall and Isles of Scilly cases 67 2021-04-17 1.1 1.4 1.7
Hammersmith and Fulham cases 58 2021-04-17 1.0 1.3 1.7
East Sussex cases 51 2021-04-17 0.9 1.3 1.7
Kensington and Chelsea cases 56 2021-04-17 0.9 1.2 1.5
Derry City and Strabane cases 162 2021-04-17 1.0 1.2 1.4
Lambeth cases 58 2021-04-17 0.9 1.2 1.5
South Lanarkshire cases 150 2021-04-17 1.0 1.1 1.3
Belfast cases 113 2021-04-17 0.9 1.1 1.3
Enfield cases 59 2021-04-17 0.8 1.1 1.4
Liverpool cases 91 2021-04-17 0.9 1.1 1.3
Cambridgeshire cases 192 2021-04-17 0.9 1.1 1.2
Cheshire East cases 67 2021-04-17 0.8 1.1 1.3
Newry, Mourne and Down cases 103 2021-04-17 0.8 1.0 1.3
Bolton cases 144 2021-04-17 0.9 1.0 1.2
Cumbria cases 75 2021-04-17 0.8 1.0 1.3
Brent cases 100 2021-04-17 0.8 1.0 1.3
Norfolk cases 135 2021-04-17 0.9 1.0 1.2
Bournemouth, Christchurch and Poole cases 53 2021-04-17 0.8 1.0 1.3
Merton cases 51 2021-04-17 0.8 1.0 1.3
City of Edinburgh cases 100 2021-04-17 0.8 1.0 1.3
Bristol, City of cases 103 2021-04-17 0.8 1.0 1.2
Dudley cases 88 2021-04-17 0.8 1.0 1.2
Devon cases 70 2021-04-17 0.8 1.0 1.2
Sefton cases 52 2021-04-17 0.7 1.0 1.2

7.2 Risk Quadrants

The plots below show weekly cases (or deaths) on the X-axis and the reproduction number on the Y-axis. By dividing this into 4 quadrants we can identify upper tier local authorities with high cases and high reproduction numbers, or high cases and low reproduction numbers etc.

Values where the reproduction number exceeds 3 are plotted at 3.

7.2.1 Cases

Risk Quadrants - Cases

7.2.2 Deaths

Risk Quadrants - Deaths

7.3 Map of Effective Reproduction Number (Cases)

Below we plot the current effective reproduction number estimated from case data on maps with boundaries provided by [7].

7.4 Map of Reproduction Number by Upper Tier Local Authority Over 60 days

Below the reproduction number by week for each Upper Tier Local Authority is animated over last 60 days:

8 Detailed Results

Detailed output are saved to a comma-separated value file. The file can be found here.

9 Discussion

Limitation of this method to estimate \(R_{t,m}\) are noted in [1]

  • It’s sensitive to changes in transmissibility, changes in contact patterns, depletion of the susceptible population and control measures.
  • It relies on an assumed generation interval assumptions.
  • The size of the time window can affect the volatility of results.
  • Results are time lagged with regards to true infection, more so in the case of the use of deaths.
  • It’s sensitive to changes in case (or death) detection.
  • The generation interval may change over time.

Further to the above the estimates are made under assumption that the cases and deaths are reported consistently over time. For cases this means that testing needs to be at similar levels and reported with similar lag. Should these change rapidly over an interval of a few weeks the above estimates of the effective reproduction numbers would be biased. For example a rapid expansion of testing over the last 3 weeks would results in overestimating recent effective reproduction numbers. Similarly any changes in reporting (over time and underreporting) of deaths would also bias estimates of the reproduction number estimated using deaths. It may well be that some catch-up in reported deaths is exaggerating the estimates for October.

Estimates for the reproduction number are plotted in time period in which the relevant measure is recorded. Though in reality the infections giving rise to those estimates would have occurred roughly between a week to 4 weeks earlier depending on whether it was cases or deaths. These figures have not been shifted back.

Despite these limitation we believe the ease of calculation of this method and the ability to use multiple sources makes it useful as a monitoring tool.

10 Author

This report was prepared by Louis Rossouw. Please get in contact with Louis Rossouw if you have comments or wish to receive this regularly.

Louis Rossouw
Head of Research & Analytics
Gen Re | Life/Health Canada, South Africa, Australia, NZ, UK & Ireland
Email: LRossouw@GenRe.com Mobile: +27 71 355 2550

The views in this document represents that of the author and may not represent those of Gen Re. Also note that given the significant uncertainty involved with the parameters, data and methodology care should be taken with these numbers and any use of these numbers.

11 Digital boundaries

Office for National Statistics licensed under the Open Government Licence v.3.0

Contains OS data © Crown copyright and database right 2020

References

[1] A. Cori, N. M. Ferguson, C. Fraser, and S. Cauchemez, “A new framework and software to estimate time-varying reproduction numbers during epidemics,” American Journal of Epidemiology, vol. 178, no. 9, pp. 1505–1512, Sep. 2013, doi: 10.1093/aje/kwt133. [Online]. Available: https://doi.org/10.1093/aje/kwt133

[2] A. Cori, EpiEstim: A package to estimate time varying reproduction numbers from epidemic curves. 2013 [Online]. Available: https://CRAN.R-project.org/package=EpiEstim

[3] Office for National Statistics, “Official UK Coronavirus Dashboard,” 2020. [Online]. Available: https://coronavirus.data.gov.uk. [Accessed: 07-Nov-2020]

[4] Office for National Statistics, “Countries (December 2019) Boundaries UK BUC,” 09-Oct-2017. [Online]. Available: https://geoportal.statistics.gov.uk/search?collection=Dataset. [Accessed: 07-Nov-2020]

[5] Office for National Statistics, “NUTS Level 1 (January 2018) Ultra Generalised Clipped Boundaries in the United Kingdom,” 31-Jul-2017. [Online]. Available: https://geoportal.statistics.gov.uk/datasets/nuts-level-1-january-2018-ultra-generalised-clipped-boundaries-in-the-united-kingdom. [Accessed: 07-Nov-2020]

[6] Office for National Statistics, “NHS England Regions (April 2020) Boundaries EN BUC,” 13-May-2020. [Online]. Available: https://geoportal.statistics.gov.uk/search?collection=Dataset. [Accessed: 07-Nov-2020]

[7] Office for National Statistics, “Counties and Unitary Authorities (December 2019) Boundaries UK BUC,” 11-Mar-2020. [Online]. Available: https://geoportal.statistics.gov.uk/datasets/counties-and-unitary-authorities-december-2019-boundaries-uk-buc. [Accessed: 07-Nov-2020]